?? freq_pat.m
字號(hào):
function lst = freq_pat(H,pat)% freq_pat.m - generate frequency partition%% input:% H: half length of the frequency span, H needs to be greater than 16% pat: type of frequency partition which satsifies parabolic scaling relationship% equal to 'p' or 'q'%% output:% lst: data representing the partition of frequency%% Written by Lexing Ying and Laurent Demanet, 2006 if(H<16) error('H needs to be at least 16'); end if( pat=='p') %parabolic scaling by lexing len = ceil(log2(H)/2)+1; lst = cell(len,1); lst{1} = [1 1]; lst{2} = [0 1]; lst{3} = [0 1 1 1]; cnt = 16; idx = 3; rad = 4; while(cnt<H) old = cnt; lst{idx} = [lst{idx} 1 1]; cnt = cnt + 2*rad; idx = idx+1; rad = 2*rad; trg = min(4*old,H); lst{idx} = [zeros(1,cnt/rad), ones(1,(trg-cnt)/rad)]; cnt = trg; end elseif(pat=='q') %parabolic scaling by laurent len = floor(log2(H)/2)+1; lst = cell(len,1); lst{1} = [1 1]; lst{2} = [0 1 1 1]; cnt = 8; idx = 2; rad = 2; while(cnt<H) old = cnt; lst{idx} = [lst{idx} 1 1]; cnt = cnt + 2*rad; idx = idx+1; rad = 2*rad; trg = min(4*old,H); lst{idx} = [zeros(1,cnt/rad), ones(1,(trg-cnt)/rad)]; cnt = trg; end elseif(pat=='u') len = ceil(log2(H)/2)+1; %uniform partitioning lst = cell(len,1); B = 2^(len-1); lst{end} = ones(1,H/B); else error('wrong pat'); end
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